Description

Theory
2

Laboratory
3

Instructors

Maria Teresa Costa

Contents

CP1. Introduction to Operations Research (5%)
Motivation
Methodology
Examples

CP2. Modeling programming problems (LP, ILP, MILP, BILP) (30%)
Variables, parameters, objective and constraints
Mathematical formulation
Symbolic notation
Special Cases

CP3. LP Problem Solving Techniques (40%)
Graphical method
Primal simplex method
Specific Algorithms of Particular Cases
Using appropriate software

CP4. Case studies (25%)
Examples of application in various areas of Engineering

Learning Outcomes

The main objective of the course is to prepare the student to address the complex problems of real life, identifying components that may be represented as models or associations of mathematical models, and sensitizing them to the selection of a resolution tool between the vast repertoire of tools that comprise the field of Operational Research.
It is intended that a student is able to apply concepts in addressing small real cases, including:
OB1. Interpret and identify the problem
OB2. Build an appropriate mathematical model
OB3. For small problems, apply appropriate analytical methods of resolution
OB4. For larger problems, use appropriate software (namely by using Excel Solver)
OB5. For large-scale applications, implement in OR-Tools da Google
OB6. Provide a critical analysis of the results in order to support decision-making
OB7. Develop a structured report